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recommend_skills

Review read-only latent skill recommendations captured by explicit tracked evidence. Use dry-run for safe inspection without mutation.

Instructions

Review read-only latent skill recommendations captured by explicit skills.track evidence.

This never promotes, imports, syncs, creates, or mutates skills. dry_run is accepted for API clarity; non-read-only behavior is not supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoproject
dry_runNo
min_recurrenceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses critical behavioral traits: read-only, no mutations, and that dry_run is accepted for clarity but non-read-only behavior not supported. This fully informs the agent of safety boundaries. It could add details about return format or auth, but output schema exists to cover return.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. First sentence states core purpose; second clarifies constraints. Front-loaded and every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters (0% schema coverage), no annotations, and an output schema, the description adequately covers the read-only behavior but fails to explain scope and min_recurrence. The output schema might document return values, so that gap is mitigated. However, for full completeness, parameter explanations are needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It only explains dry_run's purpose ('accepted for API clarity'), but omits meaning for scope and min_recurrence. For a 3-parameter tool with no schema descriptions, this is insufficient. The agent cannot infer the role of scope or min_recurrence.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool reviews read-only latent skill recommendations, using specific verb 'review' and resource. It explicitly distinguishes from siblings by listing actions it never performs (promotes, imports, syncs, creates, mutates), which is exceptional differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description provides clear context that the tool is read-only and never mutates, implying it should be used for viewing recommendations. However, it lacks explicit when-to-use vs alternatives, such as mentioning promote_skill_recommendation for promotion. The negative list ('never promotes...') serves as when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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